Efficient convex optimization method for underwater passive source localization based on RSS with WSN

Yan, Ye; Wang, Haiyan; Shen, Xiaohong; Yang, Fuzhou; Chen, Zhao

doi:10.1109/icspcc.2012.6335673

Cited by 25 publications

(20 citation statements)

References 14 publications

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“…Under a centralized processing mode, all sensors convey their RSS measurements with respect to the target node to the central processor. We assume that the locations of all the nodes are supposed to be unchanged during the computation period [11,15]. Figure 1 shows the i-th sensoring link in the UWSN model.…”

Section: The System Modelmentioning

confidence: 99%

“…Additionally, as AoA relies on a direct line-of-sight path from the target node to anchor nodes, it will cause large errors in AoA measurements in multi-path underwater acoustic (UWA) transmission environments [7,8]. Therefore, RSS-based target localization is preferred by researchers due to its low complexity and easy implementation [9][10][11][12]. Based on the received signal strength measurements, the maximum likelihood (ML) method is used to estimate the target position [13], and this method is robust in underwater environments.…”

Section: Introductionmentioning

confidence: 99%

“…In [9], the authors propose a fast iteration algorithm by using a triangulation method based on RSS measurements. In [11], the authors discuss the convex optimization method for target localization in UWSN, while the propagation model is still the terrestrial acoustic wave model. Two convex methods based respectively on RSS-based and frequency-dependent differential approaches in UWSN have been proposed [12].…”

Section: Introductionmentioning

confidence: 99%

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Target Localization in Underwater Acoustic Sensor Networks Using RSS Measurements

Chang

et al. 2018

Applied Sciences

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This paper addresses the target localization problems based on received signal strength (RSS) measurements in underwater acoustic wireless sensor network (UWSN). Firstly, the problems based on the maximum likelihood (ML) criterion for estimating target localization in cases of both known and unknown transmit power are respectively derived, and fast implementation algorithms are proposed by transforming the non-convex problems into a generalized trust region subproblem (GTRS) frameworks. A three-step procedure is also provided to enhance the estimation accuracy in the unknown target transmit power case. Furthermore, the Cramer-Rao lower bounds (CRLBs) in both cases are derived. Computer simulation results show the superior performance of the proposed methods in the underwater environment.

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Section: The System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Target Localization in Underwater Acoustic Sensor Networks Using RSS Measurements

Chang

et al. 2018

Applied Sciences

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“…Conventional algorithms estimated the MS position through the range or angle measurement, such as time of arrival (TOA) [4] [5], time difference of arrival (TDOA) [2], time sum of arrival (TSOA) [6], [7], radio signal strength (RSS) [8], angle of arrival (AOA) [9] and the hybrid TOA/AOA [10]. All these methods must be affected by both the measurement noise and the non-line-of-sight (NLOS) error.…”

mentioning

confidence: 99%

Accurate and Simple Wireless Localizations Based on Time Product of Arrival in the DDM-NLOS Propagation Environment

Hua

Meng

Zhou

et al. 2015

IEEE J. Sel. Top. Signal Process.

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Wireless localization has become an important issue in internet of things. However, its performance degrades significantly when there are only non-line-of-sight (NLOS) propagation paths instead of line-of-sight (LOS) propagation paths. Therefore, this paper proposes a novel localization algorithm to improve the localization accuracy, where we assume that the NLOS error satisfies the requirement of distance dependent model (DDM). In order to obtain a stronger NLOS tolerance than conventional methods, the proposed algorithm analyzes the localization geometry and employs a new localization parameter, namely the time product of arrival (TPOA), to construct the linear localization equation group (LLEQ). Meanwhile, a simple least-squares (LS) principle is applied to solve this LLEQ, resulting in a low complexity. We verify our algorithm by computer simulations, and the result demonstrates that the proposed algorithm yields a better performance than traditional algorithms in the NLOS-DDM environment.Index Terms-Distance dependent model, non-line-of-sight error, time product of arrival, wireless localization.

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“…For the RSS localization technique, the transmit power and path loss exponent (PLE) are two critical parameters which have significant effects on the positioning accuracy. Many RSS methods and performance analyses have been reported in the literature [10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

RSS based method for sensor localization with unknown transmit power and uncertainty in path loss exponent

Li¹,

Huang

2016

2016 8th IEEE International Conference on Communication Software and Networks (ICCSN)

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Abstract:The localization of a sensor in wireless sensor networks (WSNs) has now gained considerable attention. Since the transmit power and path loss exponent (PLE) are two critical parameters in the received signal strength (RSS) localization technique, many RSS-based location methods, considering the case that both the transmit power and PLE are unknown, have been proposed in the literature. However, these methods require a search process, and cannot give a closed-form solution to sensor localization. In this paper, a novel RSS localization method with a closed-form solution based on a two-step weighted least squares estimator is proposed for the case with the unknown transmit power and uncertainty in PLE. Furthermore, the complete performance analysis of the proposed method is given in the paper. Both the theoretical variance and Cramer-Rao lower bound (CRLB) are derived. The relationships between the deterministic CRLB and the proposed stochastic CRLB are presented. The paper also proves that the proposed method can reach the stochastic CRLB.

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Efficient convex optimization method for underwater passive source localization based on RSS with WSN

Cited by 25 publications

References 14 publications

Target Localization in Underwater Acoustic Sensor Networks Using RSS Measurements

Target Localization in Underwater Acoustic Sensor Networks Using RSS Measurements

Accurate and Simple Wireless Localizations Based on Time Product of Arrival in the DDM-NLOS Propagation Environment

RSS based method for sensor localization with unknown transmit power and uncertainty in path loss exponent

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